In this paper, we integrate intra-channel image warping with cross-channel correlation, and show that our approach significantly improve the warping accuracy at very low cost. The proposed integration scheme is inspired by the Malvar-He-Cutler High Quality Linear Interpolation (HQLI) demosaicking method [1]}, which is probably the fastest demosaicking algorithm in the literature (except the Nearest Neighbour and Bilinear interpolation), but its trade-off between accuracy and speed is superior to many sophisticated algorithms [2]}. We first examine the potential of cross-channel correlation for image warping, by applying HQLI to postprocess color images upsampled with intra-channel interpolation. We then generalize this combination to formulate general color image warping. The performance of our method is assessed in the scenario of image super-resolution, as it is the most active sub-area of image warping. Despite its very low cost, the proposed algorithm achieves comparable accuracy to state of the art algorithms at about 40 times faster speed. Compared to CNN-based methods, our model has the flexibility of resizing the image to arbitrary size. These features are desirable for real time interactive applications on multimedia devices that have limited computation power (e.g., mobile smart phones).
